There are as many different
cancers as there are people with cancer. Unlike infectious diseases, which are
caused by pathogens that are foreign to our bodies (bacteria, viruses, parasites),
cancer cells arise from our body—our own cells gone rogue. Because cancer is a
dysfunction of a person’s normal cells, every cancer reflects the genetic
differences that mark us as individuals. Add to that environmental influences like
diet, tobacco use, the microbiome and even occupation, and the likelihood of
finding a “single” pharmaceutical cure for cancer becomes virtually impossible.
But, while looking for a single cure for all cancers may not be a fruitful activity, defining a best practice for understanding the genetic and protein biomarkers of individual tumors is proving worthwhile.
The 2018 Nobel Prize in Physiology and Medicine was awarded to James P. Allison of the United States and Tasuku Honjo of Japan for their work to identify pathways in the immune system that can be used to attack cancer cells (1). Although immunotherapy for cancer has been a goal for many decades, Dr. Allison and Dr. Honjo succeeded through their manipulation of “checkpoint inhibitor” pathways to target cancer cells.
Immune checkpoint inhibitor drugs have been effective in cancers such as aggressive metastatic melanoma, some lung cancers, kidney, bladder and head and neck cancers. These therapies have succeeded in pushing many aggressive cancers below detectable limits, though these cases are notably not relapse-free or necessarily “cured” (2,3).
One challenge in implementing immunotherapy in a cancer treatment regime is the need to understand the genetic makeup of the tumor. Certain tumors, with specific genetic features, are far more likely to respond to immune checkpoint therapy than others. For this reason, Microsatellite Instability (MSI) analysis has become an increasingly relevant tool in genetic and immuno-oncology research.